RCNN: The idea behind Recurrent Convolutional Neural Network (RCNN) [1]}, is to apply a recurrent network structure to text classification that requires no human-designed features. The recurrent structure captures contextual information as far as possible when learning word representations whilst having less noise when compared to methods that use neural networks that rely on window-based processing. To store the context, the RCNN uses a bi-directional recurrent structure and employs a max-pooling layer to capture key features present in the text automatically.
